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Table 3 Quantitative statistics analysis from Fig. 7

From: Automatic detection of human gait events: a simple but versatile 3D algorithm

 

Foot strike

Foot off

Lower whisker

Median

Upper whisker

p-value

Lower whisker

Median

Upper whisker

p-value

MC7*

− 1 [− 2 − 1]

0 [0 0]

2 [2 3]

< 0.001*

− 2 [− 5 − 2]

0 [0 0]

1 [1 3]

< 0.001*

MC6*

(no Hallux)

− 1 [− 2 − 1]

0 [0 0]

2 [2 3]

< 0.001

− 8 [− 9 − 8]

− 2 [− 2 − 2]

2 [2 4]

< 0.001

MC6*

(no Heel)

− 3 [− 4 − 3]

2 [2 2]

8 [8 9]

< 0.001

− 2 [− 5 − 2]

0 [0 0]

1 [1 3]

< 0.001

MC4*

− 1 [− 2 − 1]

0 [0 0]

2 [2 3]

< 0.001

− 2 [− 5 − 2]

0 [0 0]

1 [1 3]

< 0.001

MC2*

− 1 [− 2 − 1]

0 [0 0]

2 [2 3]

< 0.001

− 5 [− 5 − 5]

0 [0 0]

3 [3 3]

< 0.001

  1. p-values are calculated, from repeated measures ANOVA and associated post-hoc tests, on mean and variance (with an \(\alpha\)-value set to 0.05). 95% confidence intervals are calculated, from bootstrap method, on lower whisker, median and upper whisker. Units are in frames. p-value* is the global one, while the others p-value come from post-hoc tests. Results from bootstrap methods are displayed as Median [2.5% 97.5%] percentiles
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Journal of NeuroEngineering and Rehabilitation

ISSN: 1743-0003

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